In this paper, an algorithm to design a shortest-time route for a ship to avoid a tropical cyclone (TC) is proposed. The proposed algorithm takes into account the influence of the changing winds and sea waves on ship's speed and the corresponding risk using the forecasts from a numerical weather prediction model. Experimental results show that the new algorithm is able to save more time comparing with the traditional sector diagram typhoon avoidance method. In the application of the new algorithm to the navigation practice, the distance between adjacent alternative waypoints should be adjusted to meet the navigational needs, and the route should be updated simultaneously with TC forecasts from a numerical weather prediction model.

This research is supported by the National Science Foundation of China (NSFC) through Grants 51209166 and 41076009, State Key Laboratory of Tropical Oceanography (South China Sea Institute of Oceanology, Chinese Academy of Science) and self-determined and innovative research funds of WUT.
; This research is supported by the National Science Foundation of China (NSFC) through Grants 51209166 and 41076009, State Key Laboratory of Tropical Oceanography (South China Sea Institute of Oceanology, Chinese Academy of Science) and self-determined and innovative research funds of WUT.
; This research is supported by the National Science Foundation of China (NSFC) through Grants 51209166 and 41076009, State Key Laboratory of Tropical Oceanography (South China Sea Institute of Oceanology, Chinese Academy of Science) and self-determined and innovative research funds of WUT.
; This research is supported by the National Science Foundation of China (NSFC) through Grants 51209166 and 41076009, State Key Laboratory of Tropical Oceanography (South China Sea Institute of Oceanology, Chinese Academy of Science) and self-determined and innovative research funds of WUT.

This research is supported by the National Science Foundation of China (NSFC) through Grants 51209166 and 41076009, State Key Laboratory of Tropical Oceanography (South China Sea Institute of Oceanology, Chinese Academy of Science) and self-determined and innovative research funds of WUT.
; This research is supported by the National Science Foundation of China (NSFC) through Grants 51209166 and 41076009, State Key Laboratory of Tropical Oceanography (South China Sea Institute of Oceanology, Chinese Academy of Science) and self-determined and innovative research funds of WUT.
; This research is supported by the National Science Foundation of China (NSFC) through Grants 51209166 and 41076009, State Key Laboratory of Tropical Oceanography (South China Sea Institute of Oceanology, Chinese Academy of Science) and self-determined and innovative research funds of WUT.
; This research is supported by the National Science Foundation of China (NSFC) through Grants 51209166 and 41076009, State Key Laboratory of Tropical Oceanography (South China Sea Institute of Oceanology, Chinese Academy of Science) and self-determined and innovative research funds of WUT.